Introduction to Big Data
Welcome to the introduction to Big data!!! Here you will learn what is Big data? The actual definition of Big data. Big data is the combination of all types of data such as structured, semi-structured, and unstructured data collected using various methods and organizations This data or Big data can be further processed to fetch information, which is further used in machine learning techniques and training various models that depend on this data, in deep learning and data analysis projects. Big data is very helpful in doing predictive analysis or modeling. Why is it so? Big data means there is a large amount of data that is collected using methods. These methods are reliable and very advanced, thus the data received is quite accurate and the information obtained from this can give us very good results and we can predict the outcomes of related tasks. This one application of Big data is quite useful and a key reason why we or most people learn Big data. I hope this would be a good experience and keep learning.
Waves of Managing Data
After diving into the ocean we do encounter the waves, and here as well we reached the waves of managing the data. How can we manage the data? make a habit of hearing this question now and then. You will be asked as well, How are you going to manage the data?
We will explain to you how data is actually managed and how you can manage it.
Big Data Architecture
This includes the concepts related to big data architecture and the foundations for it. It further explains in-depth performance matters. There is various traditional and advanced analytics for it. We will be covering all these in this article in brief and explaining in depth what is big data architecture.
Setting the Architectural Foundation
Let's learn about the architectural foundation in detail to learn more about big data architecture.
Types of Big Data
What are actually the types of data that you would be dealing with? One needs to have a clear idea about the big data types which he will be working with and how to work each time of data. This article will cover such types of big data types and also compare them as well. We will also see if these data types can be further integrated and if so and into what and what are those integrated data types.
Integrating Data Types
Integrated data types cover the integrated types of big data such as connectors and Metadata. We will be telling you what are these and how big data i
Big Data Technology Components
We have various technology components that are associated with big data directly or indirectly. But what are these actually? we will be explaining these under this article and how these components use big data.
Virtualization Concepts
Here we will talk about the concept of making something virtually the same as the original version. We will explain how virtualization is helpful when dealing with big data.
Characteristics of Virtualization
This blog series revolves around the concept of virtualization characteristics. It includes an explanation of three characteristics of virtualization
Cloud and Big Data
When talking about big data, usually the concept of the cloud is brought up. We all visualize how the cloud is helpful when dealing with big data. This article covers these concepts of the cloud and shows the cloud deployment models and delivery models. We will be covering cloud in big data deeply so sit tight and take notes.
Big Data Techniques
Hey Fella, let's see what are the big data techniques. There are many inner concepts of big data or we refer to it as techniques of big data. This includes parallelism, storage, distribution of data, speedy networks, performance computing, and how machine learning is related to big data. You know you can visualize the data as well. It is a whole new concept and helpful in the analysis of your data and is like displaying data on a bar chart or pie chart. This makes it easy to see our data, rather than old excel sheets.
Handling Big Data
One of the key concepts other than collecting, and storing big data is handling the big data. You can collect and store the data but how to handle it is one of the concepts which is not much explored due to its complexity and varied nature. Let's take a brief look at how can we handle big data.
